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Organic Polymer-Based Photodiodes for Optoelectronic Reservoir Computing with Time-Based Coding
被引:1
作者:
Wan, Xiang
[1
]
Yan, Jie
[1
]
Wang, Runfeng
[1
,2
]
Chen, Kunfang
[1
]
Ji, Tingting
[1
]
Chen, Xin
[1
]
Chen, Lijian
[1
]
Zhu, Li
[1
,2
]
Khim, Dongyoon
[1
]
Yu, Zhihao
[1
,2
]
Sun, Liuyang
[3
]
Sun, Huabin
[1
,2
]
Tan, Chee Leong
[1
,2
]
Xu, Yong
[1
,2
]
机构:
[1] Nanjing Univ Posts & Telecommun, Coll Integrated Circuit Sci & Engn, Nanjing 210023, Peoples R China
[2] Inst Integrated Circuit & Syst, Guangdong Greater Bay Area, Guangzhou 510535, Peoples R China
[3] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Shanghai 200050, Peoples R China
来源:
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
|
2024年
/
15卷
/
40期
基金:
中国国家自然科学基金;
关键词:
SENSOR;
D O I:
10.1021/acs.jpclett.4c02571
中图分类号:
O64 [物理化学(理论化学)、化学物理学];
学科分类号:
070304 ;
081704 ;
摘要:
The integration of optoelectronic devices with reservoir computing offers a novel and effective approach to in-sensor computing. This work presents a hybrid digital-physical solution that leverages the high-performance poly[(bithiophene)-alternate-(2,5-di(2-octyldodecyl)-3,6-di(thienyl)-pyrrolyl pyrrolidone)] (DPPT-TT) organic polymer-based photodiodes for the hardware implementation of reservoir computing system. The photodiodes demonstrate nonlinear photoelectric responses, fading memory, and cyclical stability, in relation to the temporal information on light stimuli. These attributes enable effective mapping, historical context sensitivity, and consistent performance, with time-encoded inputs, which are particularly essential for accurate and continuous processing of time series data. The optoelectronic reservoir computing system with pulse width modulation (PWM) coding demonstrates impressive performance in the prediction of chaotic sequences, achieving a normalized root-mean-square error as low as 0.095 with optimized parameters. The DPPT-TT-based photodiodes and time-based coding offer a hardware-efficient solution for reservoir computing, significantly advancing Internet of Things applications.
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页码:10162 / 10168
页数:7
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